The discovery of antibiotics nearly 80 years ago was a major milestone in the battle against infectious disease, yet bacterial infections continue to be a significant cause of death worldwide. In fact, management of many bacterial infections is becoming progressively more difficult due to the emergence of new and rapidly evolving pathogens with increased virulence, resistance to antibiotics, a greater ability to evade host responses, and heightened transmissibility. To reverse this trend, a systematic understanding of the complex dynamics between the pathogen and host is needed at every level of interaction, including those between cells, individuals, microbial communities, and populations. We will develop and implement an integrated experimental framework that provides systematic and complementary insights into bacterial infections encompassing single cells, animal models, and human patients, to investigate cellular genomics, transcriptional networks, and host microecologies. Three of the most deadly and costly bacterial pathogens will be used as examples to develop this framework and probe the host-pathogen interaction. Specifically, we will dissect the interaction between Mycobacterium tuberculosis and its host at the single cell level to gain a deep and highly resolved characterization of the host cellular states that contribute to susceptibility to infection. We will follow the dynamics of uropathogenic Escherichia coli (UPEC) infection in animals and humans to gain insights into the role of UPEC, the host and the host microbiome in the persistence of recurrent urinary tract infections. We will track the movement and evolution of carbapenem resistant Enterobacteriaceae (CRE) as they emerge in patient populations contributing critical details about how CRE and the resistance elements that they carry are transmitted among patients and patient populations. There are two goals of this work. One is to develop an adaptable framework of multi-omic approaches to be applied to a wide-range of pathogens for the dissection of bacterial infection at the single cell, infected individual and clinical population levels. The second is to capitalize on the output from this framework to identify points